If you look around the Serverless Application Repository console, you will find a number of applications that can help you ship logs from CloudWatch Logs to external services. One such example is the LogzioCloudWatchShipper application below.

With AWS Lambda, we get blue-green deployment out of the box. After we update our code, requests against our function would be routed to the new version. The platform would then automatically dispose of all containers running the old code to free up resources.

AWS Lambda has a soft limit of 75GB for deployment packages for all your functions (including the layers you use). This might seem a lot, but a team that has fully embraced serverless can reach this limit very quickly.

With AWS Lambda, we can deploy and scale individual functions. However, we as engineers still like to think in terms of services and maintain a mapping between business capabilities and service boundaries. The service level abstraction makes it easier for us to reason about large systems. As such, cohesive functions that work together to serve a business feature are grouped together and deployed as a unit (i.e. a service) through CloudFormation.

In the world of web applications, Web Frameworks (WF) existed for a very long time. Traditional WF existed in a world without the notion of microservices, let alone the notion of serverless. Many first-time serverless users use WF to ease the transition into the ecosystem, sometimes unaware of its effect on the performance. The following post focuses on potential cold start issues when using WF in the NodeJS ecosystem.

With AWS Lambda, deploying a new version of our application has never been simpler. However, we still need to take care of some underlying plumbing. Such as managing the configuration for our functions as well as other related resources such as API Gateway, CloudWatch log groups and IAM policies. Depending on the event sources you would like to use, you also need to provision the necessary EventSourceMapping in order to use Lambda with the likes of Kinesis Streams and SQS.

AWS introduced Lambda Layers at re:invent 2018 as a way to share code and data between functions within and across different accounts. It’s a useful tool and something many AWS customers have been asking for. However, since we already have numerous ways of sharing code, including package managers such as NPM, when should we use Layers instead?

Last week I attended ServerlessConf SF. This was the 8th and largest ServerlessConf to date with more than 550 attendees. The conference had an effective agenda with a strong slate of talks and an impressive presence of community thought leaders. Kudos to the ACloudGuru team for organizing the event!